In preparation for this post, I asked my fifteen-year old grandson to define product logistics and product supply chain.  He looked at me as though I had just fallen off a turnip truck.  I said you know, how does a manufacturer or producer of products get those products to the customer—the eventual user of the device or commodity.  How does that happen? I really need to go do my homework.  Can I think about this and give you an answer tomorrow?

SUPPLY CHAIN LOGISTICS:

Let’s take a look at Logistics and Supply Chain Management:

“Logistics typically refers to activities that occur within the boundaries of a single organization and Supply Chain refers to networks of companies that work together and coordinate their actions to deliver a product to market. Also, traditional logistics focuses its attention on activities such as procurement, distribution, maintenance, and inventory management. Supply Chain Management (SCM) acknowledges all of traditional logistics and also includes activities such as marketing, new product development, finance, and customer service” – from Essential of Supply Chain Management by Michael Hugos.

“Logistics is about getting the right product, to the right customer, in the right quantity, in the right condition, at the right place, at the right time, and at the right cost (the seven Rs of Logistics)” – from Supply Chain Management: A Logistics Perspective By John J. Coyle et al

Now, that wasn’t so difficult, was it?  A good way to look at is as follows:

MOBILITY AND THE SUPPLY CHAIN:

There have been remarkable advancements in supply chain logistics over the past decade.  Most of those advancements have resulted from companies bringing digital technologies into the front office, the warehouse, and transportation to the eventual customer.   Mobile technologies are certainly changing how products are tracked outside the four walls of the warehouse and the distribution center.  Realtime logistics management is within the grasp of many very savvy shippers.  To be clear:

Mobile networking refers to technology that can support voice and/or data network connectivity using wireless, via a radio transmission solution. The most familiar application of mobile networking is the mobile phone or tablet or i-pad.  From real-time goods tracking to routing assistance to the Internet of Things (IoT) “cutting wires” in the area that lies between the warehouse and the customer’s front door is gaining ground as shippers grapple with fast order fulfillment, smaller order sizes, and ever-evolving customer expectations.

In return for their tech investments, shippers and logistics managers are gaining benefits such as short-ended lead times, improved supply chain visibility, error reductions, optimized transportation networks and better inventory management.  If we combine these advantages we see that “wireless” communications are helping companies work smarter and more efficiently in today’s very fast-paced business world.

MOBILITY TRENDS:

Let’s look now at six (6) mobility trends.

  1. Increasingly Sophisticated Vehicle Communications—There was a time when the only contact a driver had with home base was after an action, such as load drop-off, took place or when there was an in-route problem. Today, as you might expect, truck drivers, pilots and others responsible for getting product to the customer can communicate real-time.  Cell phones have revolutionized and made possible real-time communication.
  2. Trucking Apps—By 2015, Frost & Sullivan indicated the size of the mobile trucking app market hit $35.4 billion dollars. Mobile apps are being launched, targeting logistics almost constantly. With the launch of UBER Freight, the competition in the trucking app space has heated up considerably, pressing incumbents to innovate and move much faster than ever before.
  3. Its’ Not Just for the Big Guys Anymore: At one time, fleet mobility solutions were reserved for larger companies that could afford them.  As technology has advanced and become more mainstream and affordable, so have fleet mobility solution.
  4. Mobility Helps Pinpoint Performance and Productivity Gaps: Knowing where everything is at any one given time is “golden”. It is the Holy Grail for every logistics manager.  Mobility is putting that goal within their reach.
  5. More Data Means More Mobile Technology to Generate and Support Logistics: One great problem that is now being solved, is how to handle perishable goods and refrigerated consumer items.  Shippers who handle these commodities are now using sensors to detect trailer temperatures, dead batteries, and other problems that would impact their cargos.  Using sensors, and the data they generate, shippers can hopefully make much better business decisions and head off problems before they occur.  Sensors, if monitored properly, can indicate trends and predict eventual problems.
  6. Customers Want More Information and Data—They Want It Now: Customer’s expectations for real-time shipment data is now available at their fingertips without having to pick up a telephone or send an e-mail.  Right now, that information is available quickly online or with a smartphone.

CONCLUSIONS: 

The world is changing at light speed, and mobility communications is one technology making this possible.  I have no idea as to where we will be in ten years, but it just might be exciting.

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TRUCKING

September 19, 2017


I have several clients I try to keep happy each week.  One is in Cleveland, Tennessee. That’s about a forty-five (45) minute drive for me, one way, so I get to see a great deal of Interstate traffic.  This is my thirteenth year with this company as a client so I have made that trip multiple times.  There is NO time of the day that I do not see an armada of fifty-three (53) foot rigs hauling their load from point “A” to point “B”.  The numbers are quite frankly staggering.  According to the American Trucking Association (ATA) for the year 2016:

  • The big rigs moved 10.42 billion tons of freight or seventy percent (70%) of all domestic freight tonnage.
  • The nation’s commercial trucks paid $41.3 billion in state and federal highway user fees and taxes. The average five-axel-trailer pays more than $5,600.00 in taxes annually.
  • There were 33.8 million trucks registered for business purposes, including 3.68 million Class 8 trucks. (NOTE: The Class 8 truck gross vehicle weight rating (GVWR) is a vehicle with a GVWR exceeding 33000 pounds (14969 kg). These include tractor trailer tractors as well as single-unit dump trucks of a GVWR over 33,000 pounds; such trucks typically have 3 or more axles.)
  • The 33.8 million trucks mentioned above burned 38.8 billion gallons of diesel fuel and 15.5 billion gallons of gasoline. Today’s average price per gallon for diesel is $2.71.
  • They traveled 450.4 billion miles.
  • Approximately 7.4 million Americans are employed in trucking-related jobs, including 3.5 million as truck drivers.
  • Trucking is an industry made up of small businesses; 91% of motor carriers operate six or fewer trucks and 97.3% operate less than 20.
  • Annual revenues for 2016 totaled $676.2 billion.
  • Freight volumes are projected to grow 2.8% in 2017 with an annual growth rate of 3.4% through 2023.
  • Truckload volumes are expected to grow 2.7% per year from 2017 to 2023.
  • Short haul or LTL shipments, will increase 3.3% per year from 2017 to 2023.

Companies, small and large, are making concerted efforts to lessen costs for diesel fuel and obtain greater efficencies thereby reducing overall total costs of operation.  This is a nationwide exercise all movers long-haul and short-haul are participating in.  We are already seeing FedEx, UPS, the Federal Post Office, DHL, police departments, taxi cab companies and others convert from diesel to propane or natural gas as the fuel of choice.  This not only reduces operating expense but reduces carbon emissions.   We also see companies who design and build engines for these big rigs, working hard to improve mileage and engine efficencies.  Progress is being made on a yearly basis.  So, the next time you pass an LTL or STL hauler, think about the industry and the efforts they are in the process of adopting to improve their company.

MULTITASKING

September 14, 2017


THE DEFINITION:

“Multitasking, in a human context, is the practice of doing multiple things simultaneously, such as editing a document or responding to email while attending a teleconference.”

THE PROCESS:

The concept of multitasking began in a computing context. Computer multitasking, similarly to human multitasking, refers to performing multiple tasks at the same time. In a computer, multitasking refers to things like running more than one application simultaneously.   Modern-day computers are designed for multitasking. For humans, however, multitasking has been decisively proven to be an ineffective way to work. Research going back to the 1980s has indicated repeatedly that performance suffers when people multitask.

REALITY:

Multitasking is not a natural human trait.  In a few hundred years, natural evolution may improve human abilities but for now, we are just not good at it.  In 2007, an ABC Evening News broadcast cited, “People are interrupted once every ten and one-half minutes (10.5).  It takes twenty-three (23) minutes to regain your train of thought.  People lose two point one (2.1) hours each day in the process of multitasking.”

A great article entitled “No Task Left Behind” by Mark Gloria, indicated that a person juggled twelve (12) work spheres each day and fifty-seven percent (57%) of the work got interrupted.  As a result, twenty-three percent (23%) of the work to be accomplished that day got pushed to the next day and beyond. That was the case twelve years ago.  We all have been there trying to get the most of each day only to return home with frustration and more to do the next day.

Experience tells us that:

  • For students, an increase in multitasking predicted poorer academic results.
  • Multitaskers took longer to complete tasks and produced more errors.
  • People had more difficulty retaining new information while multitasking.
  • When tasks involved making selections or producing actions, even very simple tasks performed concurrently were impaired.
  • Multitaskers lost a significant amount of time switching back and forth between tasks, reducing their productivity up to forty percent (40%).
  • Habitual multitaskers were less effective than non-multitaskers even when doing one task at any given time because their ability to focus was impaired.
  • Multitasking temporarily causes an IQ drop of 10 points, the equivalent of going without sleep for a full night.
  • Multitaskers typically think they are more effective than is actually the case.
  • There are limited amounts of energy for any one given day.
  • Multitasking can lessen inter-personal skills and actually detract from the total work force.
  • It encourages procrastination.
  • A distracted mind may become permanent.

THE MYTH OF MULTITASKING:

People believe multitasking is a positive attribute, one to be admired. But multitasking is simply the lack of self-discipline. Multitasking is really switching your attention from one to task to another to another, instead of giving yourself over to a single task. Multitasking is easy; disciplined focus and attention is difficult.

The quality of your work is determined by how much of your time, your focus and your attention you give it. While multitasking feels good and feels busy, the quality of the work is never what it could be with the creator’s full attention. More and more, this is going to be apparent to those who are judging the work, especially when compared to work of someone who is disciplined and who has given the same or similar project their full focus and attention.

MENTAL FLOW:

In positive psychology, flow, also known as the zone, is the mental state of operation in which a person performing an activity is fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity.

The individual who coined the phrase “flow” was Mihaly Csikszentmihalyi. (Please do NOT ask me to pronounce Dr. Csikszentmihalyi’s last name.)  He made the following statement:

“The best moments in our lives are not the passive, receptive, relaxing times… The best moments usually occur if a person’s body or mind is stretched to its limits in a voluntary effort to accomplish something difficult and worthwhile.”

– Mihaly Csikszentmihalyi  

EIGHT CHARACTERISTICS OF “FLOW”:

  1. Complete concentration on the task.  By this we mean really complete.
  2. Clarity of goals and reward in mind and immediate feedback. No need to focus and concentrate when there are no goals in mind to indicate completion.
  3. Transformation of time (speeding up/slowing down of time). When in full “flow” mode, you lost time.
  4. The experience is intrinsically rewarding, has an end itself.
  5. Effortlessness and ease.
  6. There is a balance between challenge and skills.
  7. Actions and awareness are merged, losing self-conscious rumination.
  8. There is a feeling of control over the task.

I personally do not get there often but the point is—you cannot get in the “zone”, you will not be able to achieve mental “flow” when you are in the multitasking mode.  I just will not happen.

As always, I welcome your comments.

V2V TECHNOLOGY

September 9, 2017


You probably know this by now if you read my postings—my wife and I love to go to the movies.  I said GO TO THE MOVIES, not download movies but GO.  If you go to a matinée, and if you are senior, you get a reduced rate.  We do that. Normally a movie beginning at 4:00 P.M. will get you out by 6:00 or 6:30 P.M. Just in time for dinner. Coming from the Carmike Cinema on South Terrace, I looked left and slowly moved over to the inside lane—just in time to hit car in my “blind side”.  Low impact “touching” but never the less an accident anyway.  All cars, I’m told, have blind sides and ours certainly does.  Side mirrors do NOT cover all areas to the left and right of any vehicle.   Maybe there is a looming solution to that dilemma.

V2V:

The global automotive industry seems poised and on the brink of a “Brave New World” in which connectivity and sensor technologies come together to create systems that can eliminate life-threatening collisions and enable automobiles that drive themselves.  Knows as Cooperative Intelligent Transportation Systems, vehicle-to-vehicle or V2V technologies open the door for automobiles to share information and interact with each other, as well as emerging smart infrastructure. These systems, obviously, make transportation safer but offer the promise of reducing traffic congestion.

Smart features of V2V promise to enhance drive awareness via traffic alerts, providing notifications on congestion, obstacles, lane changing, traffic merging and railway crossing alerts.  Additional applications include:

  • Blind spot warnings
  • Forward collision warnings
  • Sudden brake-ahead warnings
  • Approaching emergency vehicle warnings
  • Rollover warnings
  • Travel condition data to improve maintenance services.

Already The Department of Transportation “Vehicle-to-Vehicle Communications: Readiness of V2V Technology for Application”, DOT HS 812 014, details the technology as follows:

“The purpose of this research report is to assess the readiness for application of vehicle-to-vehicle (V2V) communications, a system designed to transmit basic safety information between vehicles to facilitate warnings to drivers concerning impending crashes. The United States Department of Transportation and NHTSA have been conducting research on this technology for more than a decade. This report explores technical, legal, and policy issues relevant to V2V, analyzing the research conducted thus far, the technological solutions available for addressing the safety problems identified by the agency, the policy implications of those technological solutions, legal authority and legal issues such as liability and privacy. Using this report and other available information, decision-makers will determine how to proceed with additional activities involving vehicle-to-vehicle (V2V), vehicle-to-infrastructure (V2I), and vehicle-to-pedestrian (V2P) technologies.”

The agency estimates there are approximately five (5) million annual vehicle crashes, with attendant property damage, injuries, and fatalities. While it may seem obvious, if technology can help drivers avoid crashes, the damage due to crashes simply never occurs.  This is the intent of an operative V2V automotive system. While these “vehicle-resident” crash avoidance technologies can be highly beneficial, V2V communications represent an additional step in helping to warn drivers about impending danger. V2V communications use on-board dedicated short-range radio communication devices to transmit messages about a vehicle’s speed, heading, brake status, and other information to other vehicles and receive the same information from the messages, with range and “line-of-sight” capabilities that exceed current and near-term “vehicle-resident” systems — in some cases, nearly twice the range. This longer detection distance and ability to “see” around corners or “through” other vehicles and helps V2V-equipped vehicles perceive some threats sooner than sensors, cameras, or radar.  This can warn drivers accordingly. V2V technology can also be fused with those vehicle-resident technologies to provide even greater benefits than either approach alone. V2V can augment vehicle-resident systems by acting as a complete system, extending the ability of the overall safety system to address other crash scenarios not covered by V2V communications, such as lane and road departure. A fused system could also augment system accuracy, potentially leading to improved warning timing and reducing the number of false warnings.

Communications represent the keystone of V2V systems.  The current technology builds upon a wireless standard called Dedicated Shor- Range Communication or DSRC.  DSRC is based upon the IEEE 802.11p protocol.  Transmissions of these systems consists of highly secure, short-to-medium-range, high-speed wireless communication channels, which enable vehicles to connect with each other for short periods of time.  Using DSRC, two or more vehicles can exchange basic safety messages, which describe each vehicle’s speed, position, heading, acceleration rate, size and braking status.  The system sends these messages to the onboard units of surrounding vehicles ten (10) times per second, where they are interpreted and provide warnings to the driver.  To achieve this, V2V systems leverage telematics to track vehicles via GPS monitoring the location, movements, behavior and status of each vehicle.

Based on preliminary information, NHTSA currently estimates that the V2V equipment and supporting communications functions (including a security management system) would cost approximately $341 to $350 per vehicle in 2020 dollars. It is possible that the cost could decrease to approximately $209 to $227 by 2058, as manufacturers gain experience producing this equipment (the learning curve). These costs would also include an additional $9 to $18 per year in fuel costs due to added vehicle weight from the V2V system. Estimated costs for the security management system range from $1 to $6 per vehicle, and they will increase over time due to the need to support an increasing number of vehicles with the V2V technologies. The communications costs range from $3 to $13 per vehicle. Cost estimates are not expected to change significantly by the inclusion of V2V-based safety applications, since the applications themselves are software and their costs are negligible.  Based on preliminary estimates, the total projected preliminary annual costs of the V2V system fluctuate year after year but generally show a declining trend. The estimated total annual costs range from $0.3 to $2.1 billion in 2020 with the specific costs being dependent upon the technology implementation scenarios and discount rates. The costs peak to $1.1 to $6.4 billion between 2022 and 2024, and then they gradually decrease to $1.1 to $4.6 billion.

In terms of safety impacts, the agency estimates annually that just two of many possible V2V safety applications, IMA (Integrated Motor Assists) and LTA (Land Transport Authority), would on an annual basis potentially prevent 25,000 to 592,000 crashes, save 49 to 1,083 lives, avoid 11,000 to 270,000 MAIS 1-5 injuries, and reduce 31,000 to 728,000 property-damage-only crashes by the time V2V technology had spread through the entire fleet. We chose those two applications for analysis at this stage because they are good illustrations of benefits that V2V can provide above and beyond the safety benefits of vehicle-resident cameras and sensors. Of course, the number of lives potentially saved would likely increase significantly with the implementation of additional V2V and V2I safety applications that would be enabled if vehicles were equipped with DSRC capability.

CONCLUSIONS: 

It is apparent to me that we are driving (pardon the pun) towards self-driving automobiles. I have no idea as to when this technology will become fully adopted, if ever.  If that happens in part or across the vehicle spectrum, there will need to be some form of V2V. One car definitely needs to know where other cars are relative to position, speed, acceleration, and overall movement. My wife NEVER goes to sleep or naps while I’m driving—OK maybe one time as mentioned previously.  She is always remarkably attentive and aware when I’m behind the wheel.  This comes from experience gained over fifty-two years of marriage.  “The times they are a-changing”.   The great concern I have is how we are to maintain the systems and how “hackable” they may become.  As I awoke this morning, I read the following:

The credit reporting agency Equifax said Thursday that hackers gained access to sensitive personal data — Social Security numbers, birth dates and home addresses — for up to 143 million Americans, a major cybersecurity breach at a firm that serves as one of the three major clearinghouses for Americans’ credit histories.

I am sure, like me, that gives you pause.  If hackers can do that, just think about the chaos that can occur if V2V systems can be accessed and controlled.  Talk about keeping one up at night.

As always, I welcome your comments.


WHERE WE ARE:

The manufacturing industry remains an essential component of the U.S. economy.  In 2016, manufacturing accounted for almost twelve percent (11.7%) of the U.S. gross domestic product (GDP) and contributed slightly over two trillion dollars ($2.18 trillion) to our economy. Every dollar spent in manufacturing adds close to two dollars ($1.81) to the economy because it contributes to development in auxiliary sectors such as logistics, retail, and business services.  I personally think this is a striking number when you compare that contribution to other sectors of our economy.  Interestingly enough, according to recent research, manufacturing could constitute as much as thirty-three percent (33%) of the U.S. GDP if both its entire value chain and production for other sectors are included.  Research from the Bureau of Labor Statistics shows that employment in manufacturing has been trending up since January of 2017. After double-digit gains in the first quarter of 2017, six thousand (6,000) new jobs were added in April.  Currently, the manufacturing industry employs 12,396,000 people, which equals more than nine percent (9%) of the U.S. workforce.   Nonetheless, many experts are concerned that these employment gains are soon to be halted by the ever-rising adoption of automation. Yet automation is inevitable—and like in the previous industrial revolutions, automation is likely to result in job creation in the long term.  If we look back at the Industrial Revolution.

INDUSTRIAL REVOLUTION:

The Industrial Revolution began in the late 18th century when a series of new inventions such as the spinning jenny and steam engine transformed manufacturing in Britain. The changes in British manufacturing spread across Europe and America, replacing traditional rural lifestyles as people migrated to cities in search of work. Men, women and children worked in the new factories operating machines that spun and wove cloth, or made pottery, paper and glass.

Women under 20 made comprised the majority of all factory workers, according to an article on the Industrial Revolution by the Economic History Association. Many power loom workers, and most water frame and spinning jenny workers, were women. However, few women were mule spinners, and male workers sometimes violently resisted attempts to hire women for this position, although some women did work as assistant mule spinners. Many children also worked in the factories and mines, operating the same dangerous equipment as adult workers.  As you might suspect, this was a great departure from times prior to the revolution.

WHERE WE ARE GOING:

In an attempt to create more jobs, the new administration is reassessing free trade agreements, leveraging tariffs on imports, and promising tax incentives to manufacturers to keep their production plants in the U.S. Yet while these measures are certainly making the U.S. more attractive for manufacturers, they’re unlikely to directly increase the number of jobs in the sector. What it will do, however, is free up more capital for manufacturers to invest in automation. This will have the following benefits:

  • Automation will reduce production costs and make U.S. companies more competitive in the global market. High domestic operating costs—in large part due to comparatively high wages—compromise the U.S. manufacturing industry’s position as the world leader. Our main competitor is China, where low-cost production plants currently produce almost eighteen percent (17.6%) of the world’s goods—just zero-point percent (0.6%) less than the U.S. Automation allows manufacturers to reduce labor costs and streamline processes. Lower manufacturing costs results in lower product prices, which in turn will increase demand.

Low-cost production plants in China currently produce 17.6% of the world’s goods—just 0.6% less

than the U.S.

  • Automation increases productivity and improves quality. Smart manufacturing processes that make use of technologies such as robotics, big data, analytics, sensors, and the IoT are faster, safer, more accurate, and more consistent than traditional assembly lines. Robotics provide 24/7 labor, while automated systems perform real-time monitoring of the production process. Irregularities, such as equipment failures or quality glitches, can be immediately addressed. Connected plants use sensors to keep track of inventory and equipment performance, and automatically send orders to suppliers when necessary. All of this combined minimizes downtime, while maximizing output and product quality.
  • Manufacturers will re-invest in innovation and R&D. Cutting-edge technologies. such as robotics, additive manufacturing, and augmented reality (AR) are likely to be widely adopted within a few years. For example, Apple® CEO Tim Cook recently announced the tech giant’s $1 billion investment fund aimed at assisting U.S. companies practicing advanced manufacturing. To remain competitive, manufacturers will have to re-invest a portion of their profits in R&D. An important aspect of innovation will involve determining how to integrate increasingly sophisticated technologies with human functions to create highly effective solutions that support manufacturers’ outcomes.

Technologies such as robotics, additive manufacturing, and augmented reality are likely to be widely adopted soon. To remain competitive, manufacturers will have to re-invest a portion of their profits in R&D.

HOW AUTOMATION WILL AFFECT THE WORKFORCE:

Now, let’s look at the five ways in which automation will affect the workforce.

  • Certain jobs will be eliminated.  By 2025, 3.5 million jobs will be created in manufacturing—yet due to the skills gap, two (2) million will remain unfilled. Certain repetitive jobs, primarily on the assembly line will be eliminated.  This trend is with us right now.  Retraining of employees is imperative.
  • Current jobs will be modified.  In sixty percent (60%) of all occupations, thirty percent (30%) of the tasks can be automated.  For the first time, we hear the word “co-bot”.  Co-bot is robotic assisted manufacturing where an employee works side-by-side with a robotic system.  It’s happening right now.
  • New jobs will be created. There are several ways automation will create new jobs. First, lower operating costs will make U.S. products more affordable, which will result in rising demand. This in turn will increase production volume and create more jobs. Second, while automation can streamline and optimize processes, there are still tasks that haven’t been or can’t be fully automated. Supervision, maintenance, and troubleshooting will all require a human component for the foreseeable future. Third, as more manufacturers adopt new technologies, there’s a growing need to fill new roles such as data scientists and IoT engineers. Fourth, as technology evolves due to practical application, new roles that integrate human skills with technology will be created and quickly become commonplace.
  • There will be a skills gap between eliminated jobs and modified or new roles. Manufacturers should partner with educational institutions that offer vocational training in STEM fields. By offering students on-the-job training, they can foster a skilled and loyal workforce.  Manufacturers need to step up and offer additional job training.  Employees need to step up and accept the training that is being offered.  Survival is dependent upon both.
  • The manufacturing workforce will keep evolving. Manufacturers must invest in talent acquisition and development—both to build expertise in-house and to facilitate continuous innovation.  Ten years ago, would you have heard the words, RFID, Biometrics, Stereolithography, Additive manufacturing?  I don’t think so.  The workforce MUST keep evolving because technology will only improve and become a more-present force on the manufacturing floor.

As always, I welcome your comments.

AN AVERAGE DAY FOR DATA

August 4, 2017


I am sure you have heard the phrase “big data” and possibly wondered just what that terminology relates to.  Let’s get the “official” definition, as follows:

The amount of data that’s being created and stored on a global level is almost inconceivable, and it just keeps growing. That means there’s even more potential to glean key insights from business information – yet only a small percentage of data is actually analyzed. What does that mean for businesses? How can they make better use of the raw information that flows into their organizations every day?

The concept gained momentum in the early 2000s when industry analyst Doug Laney articulated the now-mainstream definition of big data as the four plus complexity:

  • Organizations collect data from a variety of sources, including business transactions, social media and information from sensor or machine-to-machine data. In the past, storing it would’ve been a problem – but new technologies (such as Hadoop) have eased the burden.
  • Data streams in at an unprecedented speed and must be dealt with in a timely manner. RFID tags, sensors and smart metering are driving the need to deal with torrents of data in near-real time.
  • Data comes in all types of formats – from structured, numeric data in traditional databases to unstructured text documents, email, video, audio, stock ticker data and financial transactions.
  • In addition to the increasing velocities and varieties of data, data flows can be highly inconsistent with periodic peaks. Is something trending in social media? Daily, seasonal and event-triggered peak data loads can be challenging to manage. Even more so with unstructured data.
  • Today’s data comes from multiple sources, which makes it difficult to link, match, cleanse and transform data across systems. However, it’s necessary to connect and correlate relationships, hierarchies and multiple data linkages or your data can quickly spiral out of control.

AN AVERAGE DAY IN THE LIFE OF BIG DATA:

I picture is worth a thousand words but let us now quantify, on a daily basis, what we mean by big data.

  • U-Tube’s viewers are watching a billion (1,000,000,000) hours of videos each day.
  • We perform over forty thousand (40,000) searches per second on Google alone. That is approximately three and one-half (3.5) billion searches per day and roughly one point two (1.2) trillion searches per year, world-wide.
  • Five years ago, IBM estimated two point five (2.5) exabytes (2.5 billion gigabytes of data generated every day. It has grown since then.
  • The number of e-mail sent per day is around 269 billion. That is about seventy-four (74) trillion e-mails per year. Globally, the data stored in data centers will quintuple by 2020 to reach 915 exabytes.  This is up 5.3-fold with a compound annual growth rate (CAGR) of forty percent (40%) from 171 exabytes in 2015.
  • On average, an autonomous car will churn out 4 TB of data per day, when factoring in cameras, radar, sonar, GPS and LIDAR. That is just for one hour per day.  Every autonomous car will generate the data equivalent to almost 3,000 people.
  • By 2024, mobile networks will see machine-to-machine (M2M) connections jump ten-fold to 2.3 billion from 250 million in 2014, this is according to Machina Research.
  • The data collected by BMW’s current fleet of 40 prototype autonomous care during a single test session would fill the equivalent stack of CDs 60 miles high.

We have become a world that lives “by the numbers” and I’m not too sure that’s altogether troubling.  At no time in our history have we had access to data that informs, miss-informs, directs, challenges, etc etc as we have at this time.  How we use that data makes all the difference in our daily lives.  I have a great friend named Joe McGuinness. His favorite expressions: “It’s about time we learn to separate the fly s_____t from the pepper.  If we apply this phrase to big data, he may just be correct. Be careful out there.


Portions of the following post were taken from an article by Rob Spiegel publishing through Design News Daily.

Two former Apple design engineers – Anna Katrina Shedletsky and Samuel Weiss have leveraged machine learning to help brand owners improve their manufacturing lines. The company, Instrumental , uses artificial intelligence (AI) to identify and fix problems with the goal of helping clients ship on time. The AI system consists of camera-equipped inspection stations that allow brand owners to remotely manage product lines at their contact manufacturing facilities with the purpose of maximizing up-time, quality and speed. Their digital photo is shown as follows:

Shedletsky and Weiss took what they learned from years of working with Apple contract manufacturers and put it into AI software.

“The experience with Apple opened our eyes to what was possible. We wanted to build artificial intelligence for manufacturing. The technology had been proven in other industries and could be applied to the manufacturing industry,   it’s part of the evolution of what is happening in manufacturing. The product we offer today solves a very specific need, but it also works toward overall intelligence in manufacturing.”

Shedletsky spent six (6) years working at Apple prior to founding Instrumental with fellow Apple alum, Weiss, who serves Instrumental’s CTO (Chief Technical Officer).  The two took their experience in solving manufacturing problems and created the AI fix. “After spending hundreds of days at manufacturers responsible for millions of Apple products, we gained a deep understanding of the inefficiencies in the new-product development process,” said Shedletsky. “There’s no going back, robotics and automation have already changed manufacturing. Intelligence like the kind we are building will change it again. We can radically improve how companies make products.”

There are number examples of big and small companies with problems that prevent them from shipping products on time. Delays are expensive and can cause the loss of a sale. One day of delay at a start-up could cost $10,000 in sales. For a large company, the cost could be millions. “There are hundreds of issues that need to be found and solved. They are difficult and they have to be solved one at a time,” said Shedletsky. “You can get on a plane, go to a factory and look at failure analysis so you can see why you have problems. Or, you can reduce the amount of time needed to identify and fix the problems by analyzing them remotely, using a combo of hardware and software.”

Instrumental combines hardware and software that takes images of each unit at key states of assembly on the line. The system then makes those images remotely searchable and comparable in order for the brand owner to learn and react to assembly line data. Engineers can then take action on issues. “The station goes onto the assembly line in China,” said Shedletsky. “We get the data into the cloud to discover issues the contract manufacturer doesn’t know they have. With the data, you can do failure analysis and reduced the time it takes to find an issue and correct it.”

WHAT IS AI:

Artificial intelligence (AI) is intelligence exhibited by machines.  In computer science, the field of AI research defines itself as the study of “intelligent agents“: any device that perceives its environment and takes actions that maximize its chance of success at some goal.   Colloquially, the term “artificial intelligence” is applied when a machine mimics “cognitive” functions that humans associate with other human minds, such as “learning” and “problem solving”.

As machines become increasingly capable, mental facilities once thought to require intelligence are removed from the definition. For instance, optical character recognition is no longer perceived as an example of “artificial intelligence”, having become a routine technology.  Capabilities currently classified as AI include successfully understanding human speech,  competing at a high level in strategic game systems (such as chess and Go), autonomous cars, intelligent routing in content delivery networks, military simulations, and interpreting complex data.

FUTURE:

Some would have you believe that AI IS the future and we will succumb to the “Rise of the Machines”.  I’m not so melodramatic.  I feel AI has progressed and will progress to the point where great time saving and reduction in labor may be realized.   Anna Katrina Shedletsky and Samuel Weiss realize the potential and feel there will be no going back from this disruptive technology.   Moving AI to the factory floor will produce great benefits to manufacturing and other commercial enterprises.   There is also a significant possibility that job creation will occur as a result.  All is not doom and gloom.

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